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PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 6 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
CVPR
2011
IEEE
13 years 10 days ago
Max-margin Clustering: Detecting Margins from Projections of Points on Lines
Given a unlabelled set of points X ∈ RN belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We...
Raghuraman Gopalan, Jagan Sankaranarayanan
HT
2003
ACM
14 years 1 months ago
The connectivity sonar: detecting site functionality by structural patterns
Web sites today serve many different functions, such as corporate sites, search engines, e-stores, and so forth. As sites are created for different purposes, their structure and...
Einat Amitay, David Carmel, Adam Darlow, Ronny Lem...
ICASSP
2010
IEEE
13 years 8 months ago
Detecting local semantic concepts in environmental sounds using Markov model based clustering
Detecting the time of occurrence of an acoustic event (for instance, a cheer) embedded in a longer soundtrack is useful and important for applications such as search and retrieval...
Keansub Lee, Daniel P. W. Ellis, Alexander C. Loui
COLT
2004
Springer
14 years 2 months ago
On the Convergence of Spectral Clustering on Random Samples: The Normalized Case
Given a set of n randomly drawn sample points, spectral clustering in its simplest form uses the second eigenvector of the graph Laplacian matrix, constructed on the similarity gra...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...